Implantable cardiac devices, such as stents and septal defect closure devices are sometimes difficult to see on
angiographic X-ray projection images. We present a method to enhance the visibility of these devices in rotational X-ray
angiography acquisitions using automated marker detection and motion compensation. Automatic marker detection
allows registration of the devices in the images of the rotational run. Motion compensation is done by warping the
images to a specific reference position. Averaging multiple of those motion compensated images together with the
reference frame results in an enhanced image with improved visibility due to an increase in contrast of the device with
the background structure. This allows the clinician to look at the device from multiple angles with an improved visibility
of the device to better appreciate the 3D geometry of the device. In particular, enhancement of rotational acquisitions
compared to standard enhanced fixed-angle acquisitions allows the clinician to better perceive any asymmetry in the
deployed device.

The complete expansion of the stent during a percutaneous transluminal coronary angioplasty (PTCA) procedure is
essential for treatment of a stenotic segment of a coronary artery. Inadequate expansion of the stent is a major
predisposing factor to in-stent restenosis and acute thrombosis. Stents are positioned and deployed by fluoroscopic
guidance. Although the current generation of stents are made of materials with some degree of radio-opacity to detect
their location after deployment, proper stent expansion is hard to asses. In this work, we introduce a new method for the
three-dimensional (3D) reconstruction of the coronary stents in-vivo utilizing two-dimensional projection images
acquired during rotational angiography (RA). The acquisition protocol consist of a propeller rotation of the X-ray C-arm
system of 180°, which ensures sufficient angular coverage for volume reconstruction. The angiographic projections were
acquired at 30 frames per second resulting in 180 projections during a 7 second rotational run. The motion of the stent is
estimated from the automatically tracked 2D coordinates of the markers on the balloon catheter. This information is used
within a motion-compensated reconstruction algorithm. Therefore, projections from different cardiac phases and motion
states can be used, resulting in improved signal-to-noise ratio of the stent. Results of 3D reconstructed coronary stents in
vivo, with high spatial resolution are presented. The proposed method allows for a comprehensive and unique
quantitative 3D assessment of stent expansion that rivals current X-ray and intravascular ultrasound techniques.

We have evaluated the feasibility of polyp detection on simulated ultra low dose CT Colonography data by a computer aided polyp detection (CAD) algorithm. We compared the results of ultra low dose to normal dose data. Twenty-three extensively prepared patients were scanned in prone and supine position at 25 to 100 mAs (average 70 mAs) depending on their waist circumference. Noise was added and the scans were reconstructed at 6.25 and 1.39 mAs. To evaluate the performance of the CAD system, polyps detected by an experienced reviewer and confirmed at colonoscopy were used as ground truth. Curvature, concavity and sphericity of the colon surface were used to detect polyp candidates. Bilateral filtering was used to reduce noise. We present the results for 40 polyps of 6 mm or larger as measured during colonoscopy. The by-polyp sensitivity was 80% for medium size polyps (6-9 mm) and 97% for large polyps (10 mm or larger) at an average value of 5 false-positives per scan for normal dose data. The by-polyp sensitivity was 81% for medium size polyps and 85% for large size polyps at an average value of 5 false-positives per scan for low dose data (6.25 mAs). Finally for the ultra low dose data (1.39 mAs) we achieved a by-polyp sensitivity of 75% for medium size polyps and 97% for large polyps at an average value of 5 false-positives per scan. The conclusion of our study is that CAD for polyp detection is feasible on ultra low dose CT colonography data.

Adaptive filtering of temporally varying X-ray image sequences acquired during endovascular interventions can improve the visual tracking of catheters by radiologists. Existing techniques blur the important parts of image sequences, such as catheter tips, anatomical structures and organs; and they may introduce trailing artifacts. To address this concern, an adaptive filtering process is presented to apply temporal filtering in regions without motion and spatial filtering in regions with motion. The adaptive filtering process is a multi-step procedure. First a normalized motion mask that describes the differences between two successive frames is generated. Secondly each frame is spatially filtered using the specific motion mask to specify different types of filtering in each region. Third an IIR filter is then used to combine the spatially filtered image with the previous output image; the motion mask thus serves as a weighted input mask to determine how much spatial and temporal filtering should be applied. This method results in improving both the stationary and moving fields. The visibility of static anatomical structures and organs increases, while the motion of the catheter tip and motion of anatomical structures and organs remain unblurred and visible during interventional procedures.

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Journal of Applied Remote SensingJournal of Astronomical Telescopes Instruments and SystemsJournal of Biomedical OpticsJournal of Electronic ImagingJournal of Medical ImagingJournal of Micro/Nanolithography, MEMS, and MOEMSJournal of NanophotonicsJournal of Photonics for EnergyNeurophotonicsOptical EngineeringSPIE Reviews